01/11/05

Epidemic malaria: preparing for the unexpected

By:
Stephen Connor and Madeleine Thomson

Summary

Malaria that emerges in sudden epidemics needs to be treated differently from
when it is transmitted continuously. Outbreaks often occur in remote rural
areas, making them difficult to tackle with routine approaches to the disease.
This policy brief outlines an early warning and response system being piloted in
several African countries that could serve as a model for countries in Asia and
Latin America.

Introduction

The solution to malaria goes beyond geographical borders, as does the
disease. In some areas, where malaria transmission is continuously transmitted
(endemic), the disease is best contained by routine prevention and control
measures.

But as well as endemic disease, and in other, non-endemic areas, malaria can
also occur in sudden outbreaks, or epidemics. This can happen if environmental
conditions change and mosquitoes that carry malaria are more able to breed,
multiply, and come into contact with people.

Millions of Africans are affected by these epidemics every year, yet policies
and procedures for minimising the impact of epidemics are either non-existent or
inadequate. Part of the problem is disagreement over precisely what constitutes
an epidemic, and its causes. Making matters worse, epidemics often occur in
remote rural areas, sometimes among populations on the periphery of civil
jurisdiction, thus challenging the normal routine approaches to controlling the
disease.

To truly have an impact on the burden of malaria in sub-Saharan Africa, a new
strategy needs to be in place that prevents and minimises epidemic malaria. It
requires a degree of advanced planning, preparedness and response that has never
before been achieved. This policy brief outlines a possible way forward —
currently being implemented in sub-Saharan Africa — the Malaria Early Warning
and Response System. The system aims to predict more accurately when and where
malaria epidemics are likely to occur. If successful, the system would enable
local control services to plan and act more swiftly and effectively to minimise
casualties. It could also serve as a model for other epidemic-prone regions in
Asia and Latin America.

Identifying epidemic malaria

Endemic and epidemic malaria are often treated equally despite needing
different methods of prevention and control. Endemic malaria can be prevented
and controlled largely through routine measures, whereas epidemics require
flexibility and responsiveness to rapid change.

The greatest burden of malaria in Africa is in endemic areas where the
disease is continuously present in the community. The environment encourages
interactions between the Anopheles mosquito, malaria parasites and human
hosts: surface water in which mosquitoes can lay their eggs; humidity for adult
mosquito survival; and temperatures that allow both the mosquito and the malaria
parasite to develop. When malaria control measures are inadequate, the disease
distribution is closely linked with seasonal patterns of the climate and local
environment.

The recently growing incidence of malaria in Africa is often wrongly
attributed to epidemics. It is instead largely due to more gradual changes in
endemic areas, such as demographic changes, increasing resistance of parasites
to drugs, declining control infrastructure, co-infection with other diseases,
and poverty.

Epidemic malaria tends to occur along the geographical margins of endemic
areas, when the conditions supporting the balance between the human, parasite
and mosquito vector populations are disturbed. This leads to a sharp but
temporary increase in disease incidence. More than 124 million Africans live in
such areas, and experience epidemics causing around 12 million malaria episodes
and up to 310,000 deaths annually. [1]

Those most vulnerable to endemic malaria are young children who have yet to
acquire immunity to the disease, pregnant women whose immunity is reduced during
pregnancy, and non-immune migrants or travellers. By contrast, all age groups
are vulnerable to epidemic malaria, because their exposure to disease is so
infrequent that they have little immunity. [2]

In the case of 'classic' or 'true' epidemics, the change is brought about by
natural causes such as large-scale climate anomalies in regions where the
environment does not normally allow mosquito and parasite development.

Typically these involve desert-fringes (usually too dry to support
transmission) or highland-fringes (usually too cool). The climate anomalies are
often periodic and temporary, and there is a return to equilibrium. Examples
include the epidemics occurring in the semi-arid areas of Southern Africa in
1996-1997, East Africa in 1997-1998, and the West African Sahel in 1999-2000,
all of which were associated with wide-scale and unusually heavy rainfall. [3]
Being poorly prepared, health services often become rapidly overwhelmed, leading
to perhaps ten times more malaria-related deaths than in non-epidemic years,
across all age ranges. [2, 4]

Alternatively, some epidemics are caused by human activities, such as an
irrigation scheme in a warm, semi-arid environment; the displacement of people
between highland and lowland regions; or a breakdown in pre-existing levels of
malaria control.

Rarely, they may also follow the accidental introduction of an exotic
mosquito species. These human-induced epidemics are less likely to return to the
pre-existing equilibrium and may instead lead to endemic transmission (see
figure below).

Figure: three different epidemic scenarios

Top: A 'true' epidemic, i.e. an infrequent event occurring in
areas where the disease does not normally occur. This type of epidemic is often
associated with warm dry regions. This type of epidemic may be cyclical in
nature.

Middle: An unusually high peak in transmission in areas where
malaria is normally seasonal. This type of epidemic often happens in the
highland fringes. These epidemics may also be cyclical in nature.

Bottom:
A 'resurgent outbreak' where neglect or breakdown in control allows malaria to
try to return to its higher 'pre-control' level. This third type of epidemic may
be associated with more complex emergency situations involving political
instability and displaced populations. [14]

Analysing previous epidemics helps understand their causes and offers
opportunities for predicting and monitoring the conditions that are likely to
give rise to new epidemics. This in turn enables the creation of an epidemic
early warning system, which, when combined with a flexible control plan, can
lead to epidemic prevention. [5]

The policy context

National and district malaria control programmes in affected regions are
attempting to develop better means of predicting, preventing and controlling
malaria epidemics. The countries of the Southern African Development Community,
for example, are doing so as part of their commitment to the Abuja Targets for
the Roll Back Malaria (RBM) initiative in Africa. [6] National malaria control
services are expected to detect 60 per cent of malaria epidemics within two
weeks of onset, and respond to 60 per cent of epidemics within two weeks of
their detection. They recognise that to achieve these targets they need better
information on where epidemics are most likely to occur, and ideally some
indication of when they are likely to happen.

To help guide the process, the RBM technical support network on epidemic
prevention and control, together with partnerships between World Health
Organization inter-country programmes and national ministries of health has
developed a new Malaria Early Warning and Response System (MEWS). [7 – 11]

This system has now been tested in several countries. [3] It involves new
technologies, including seasonal climate forecasting, satellite observation of
environmental conditions, geographical information systems and analytical tools
designed to help the health sector interpret climate and surveillance data. It
also involves new policies and activities for communicating and acting on the
information obtained.

Many factors may increase a population's vulnerability to malaria epidemics,
and increase the severity of disease outcome. In sub-Saharan Africa in
particular, these include co-infection with other diseases such as HIV-AIDS, and
resistance to anti-malarial drugs. Drought, floods, food insecurity and civil
unrest can also increase vulnerability by forcing populations to move between
areas of differing levels of malaria.

Information from agencies outside the health sector, such as food security
and drought monitoring services, may help in assessing and monitoring
vulnerability. Although this does not predict an epidemic, it does indicate
whether there will be an increase in the risk and probability of more severe
disease. With this information, control services can refine and assess their
plans and capacity to respond to an epidemic.

Specific assessment tools may help in identifying which populations are most
vulnerable and therefore most in need of immediate action. They may also be used
to assess the appropriateness of management and policy decisions. [12]

Seasonal climate forecasting

Recent scientific advances, largely based on improved understanding of the
interaction between sea surface temperatures and the atmosphere, have
significantly improved our ability to predict seasonal climate several months in
advance. [6] The degree of predictive skill involved varies from region to
region, but is generally higher in the tropics.

Due to the inherent uncertainty of such predictions, control services should
collaborate with regional and national forecasting services regarding their
interpretation and implications for the coming season. This would enable them to
prepare methods to prevent infection, procure effective drug supplies, and raise
community awareness on personal protection. These could all take place before
the main rainy season and three to six months before the peak malaria season.

Environmental monitoring

Control services can also use routine information on relevant environmental
variables such as rainfall, temperatures, humidity, vegetation status
(indicating soil water availability) and flooding. [13] Although they have
shorter lead-times (one to three months) than seasonal forecasts they are
generally more reliable as they are based on direct observation.

Two sources provide the necessary information: periodic summaries from
specialist centres (usually estimated from meteorological satellites) which are
available via the Internet (e.g. http://iri.columbia.edu); and the national meteorological
services’ ground-based weather station network.

The periodic summaries are generally free of charge, whereas data from
meteorological stations may come at a price, which could present difficulties
for health services in poor countries. Control services are being encouraged to
discuss the specific information and support they may need with their national
meteorological services. Environmental information would allow control services
to focus more on local changes in conditions, which they can address with
preventative interventions such as vector control and personal protection,
including mosquito nets.

Surveillance and early detection

Epidemics need to be identified as quickly as possible to allow control
services to decide how to distribute limited resources. Good sentinel case
surveillance systems are essential for detecting any unusual increases in case
numbers, and may involve several different methods for different settings.

These may detect the early phase of an epidemic, but if used in isolation
they offer control services very short lead-times (one to three weeks) to plan
and implement prevention measures.

Once an epidemic threshold has been passed, control services need to consider
carefully whether to concentrate on ensuring drug distribution and effective
case management, or embark on mosquito control, which requires considerable time
to be effective.

Planning, preparedness and response

This most important component of MEWS encapsulates the system's primary
purpose: early and effective responses to malaria epidemics, based on advanced
planning of control and contingency measures.

Control services can plan their response by assessing the vulnerability of
communities living in epidemic-prone regions. To raise confidence and
accountability, control services also need to agree which early-warning and
detection methods to use, their interpretation, and the choice and costs of
preventative control options.

They need to identify contingency measures, the roles and responsibilities of
collaborative partners, and also to define when and how much additional national
resources they would require.

As time progresses, the development, adoption and use of the warning system
should produce knowledge to make it more 'intelligent' and capable of more
appropriate and effective responses to a malaria epidemic.

Best practice

The southern African region, which has a long history of malaria epidemics,
now has the most advanced integrated approach to epidemic malaria control based
on the evidence of the key determinants of epidemics in the region. [14 – 16]

Experience and evidence for use of an integrated warning system approach
within a national malaria control programme has been demonstrated in Botswana
over the past few years. [16]

Other countries in the Southern African Development Community consider that
this approach provides a useful framework for planning epidemic preparedness and
response strategies. The WHO Southern Africa Inter-Country Programme for Malaria
Control (SAMC) has supported them in exploring these tools further. [17]

As a result the region is now, for the second time running, preparing for the
forthcoming (2005-2006) malaria season with a regional meeting at which national
and local vulnerability is assessed in the context of the pre-rainy season
climate forecasts that have been tailored to the malaria community.

The regional and national control planners recognize that southern African
countries vary markedly in how endemic they are, or how many epidemics they
have, and also in their capacity for surveillance and control coverage.

Tanzania, for example, is a highly endemic country with about 16-19 million
cases per year. Botswana and Swaziland, by contrast, have recorded cases in the
thousands and hundreds, respectively.

Zimbabwe's political and economic crisis has recently compromised its control
programme, making its population highly vulnerable to epidemics. Meanwhile,
Mozambique and Angola, are reconstructing their control programmes, after
emerging from long-term conflict.

While an integrated MEWS approach may be relevant to certain districts in all
southern African countries, its implementation remains challenging for many.
Botswana has significant resources, a stable government and a good health
service, and has a long history of mosquito control operations to prevent
malaria. Several of its neighbours also have a history of effective mosquito
control but, with the exception of South Africa and Swaziland, have neglected to
maintain these systems in recent years.

The Global Fund for AIDS, TB and Malaria is tackling this by making
significant resources available to national malaria control programmes to
revitalise their malaria control infrastructure and strategies. In addition, the
WHO Inter-Country Programme Teams are beginning to access funds from the African
Development Bank to develop regional support for malaria control, allowing
countries to gain value added benefit from the Global Fund's investment.

This is a promising development as cross-border cooperation in malaria
control is vital: epidemic-prone areas are defined by environmental zones rather
than administrative boundaries. For example, high rainfall in Angola may cause
increased stream-flow into Botswana and Namibia, and create extensive breeding
sites for mosquitoes. Drought, food security, or a range of other factors, may
lead to people migrating across borders from one level of endemicity to another
and pose a significant increase in epidemic risk. National epidemic risk maps
should be taken to reflect the situation in neighbouring countries.

Looking forward

The successful implementation of the warning system will depend on close
communication and co-operation among several partners in the health, environment
and climate communities, as well as those involved with vulnerable populations,
such as refugee and food agencies. This needs to take place at all levels from
local to international.

Increasing our knowledge of environmentally sensitive diseases, strengthening
health systems and making them better equipped to cope with a changing
environment will help us now and in the future.

The MEWS approach will strengthen overall health information and surveillance
systems, as some other diseases are also affected both spatially and temporarily
by changes in the climate and environment.

Increasing our resilience to the threats posed by climate-sensitive diseases
today may also help increase our ability to resist new threats brought about by
any future changes in climate.

Stephen Connor and Madeleine Thomson are research scientists at the
International Research Institute for Climate and Society, The Earth Institute at
Columbia University, New York, United States.

[7] WHO. Implementation of The Global Malaria Control Strategy: report of a
WHO study group on the implementation of the Global Plan of Action for Malaria
Control 1993-2000. World Health Organisation57 (1993).

[9] WHO. Malaria Control Today: current WHO recommendations. World Health
Organisation75 (2005).

[10] WHO. Africa Malaria Report. World Health Organisation (2003).

[11] WHO. Malaria Early Warning Systems, Concepts, Indicators and Partners, A
framework for field research in Africa. WHO/Roll Back Malaria/Technical Support
Network for Prevention and Control of Malaria (2001).